Our point of departure is John Berger’s 1972 BBC documentary series and book Ways of Seeing, which had an enormous impact on both popular and academic perspectives on visual culture. Central to our proposal is Berger’s assertion that: “The relation between what we see and what we know is never settled.” The project asks in what ways does computer vision further unsettle this relation. What does the increasingly general application of AI and machine vision algorithms in platforms and software imply for human ways of learning to see? What is the relationship between learning to see and training machines to see? The research proposes to investigate what new forms of computer visual literacy might be necessary when machines intervene in the interpretation, circulation and production of images. It brings together different approaches to visual and media literacy situated in the contexts of art education, pedagogy and computer science.
Links:
Learning Experiments in Computer Vision and Visual Literacy is a public engagement project funded by The Turing Institute.
Project wiki, https://centreforthestudyof.net/vision/doku.php?id=start#project_summary
Project miro board, https://miro.com/app/board/uXjVNfMa1Js=/
Ways of Machine Seeing, special issue of AI & Society, https://link.springer.com/journal/146/volumes-and-issues/36-4
Gitlab, add link
WOMS is an ongoing collaborative project involving Geoff Cox, Andrew Dewdney, Joshua Magor (CSNI), Nicolas Malevé (Aarhus University), Anne Alexander, Alan Blackwell, Leo Impett (Cambridge Digital Humanities, University of Cambridge), Annie Davey (UCL Institute of Education), Janice McLaren, Sam Mercer (The Photographers’ Gallery), Daniel Chavez Heras (King’s College), and Yasmine Boudiaf (Justice Matrix).